Social Media as Catalyzer for Connected Health: Hype or Hope? Perspectives from IMIA Working Groups
Bibliographic record
Abstract
The Internet and social media are becoming ubiquitous technologies that are transforming the health sector. Social media has become an avenue for accessing, creating and sharing health information among patients and healthcare professionals. Furthermore, social media has become a key feature in many eHealth solutions, including wearable technologies, Big Data solutions, eLearning systems, Serious Games, Medical imaging, etc. These hyper-connected technologies are facilitating a paradigm shift towards more connected health. In this panel, representatives of different IMIA Working Groups will explore how both hope and hype contribute to social media's catalyzing role in creating connected health solutions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.026 |
| Scholarly communication | 0.023 | 0.021 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".